An Interdisciplinary Perspective on IT Services Management and Service Science
Journal of Management Information Systems
Automated self-service modeling: predictive analytics as a service
Information Systems and e-Business Management
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In service systems, variability is encountered in many components, interfaces, and entities interacting with the system. There could be variations in service system performance across different usage situations and conditions. There could be operator-introduced variations in operating the system, and there could be customer- introduced variability in service operations. Since the specific usage of the service system and the usage conditions can vary, the resultant variations in service performance can impact consumer preferences for and satisfaction with the service system. While some variability has a negative impact on customers, other kinds of variations may be preferred by customers. In designing service systems, one has to understand the sources and types of variability. Any service system that is designed should be robust to these variations both in system performances and consumer preferences and satisfaction. Achieving the robustness criteria, however, implies consideration of a large number of design criteria across multiple functions both system design and customer-facing functions. In this paper, we present the factors that need to be considered in service system design which encounter variations not only in usage, but also in operator and customer skill levels, perception of system complexity, preference and satisfaction. We identify the research issues involved and present a general framework to tackle such service system design problems. .